Appendices for “ Wavelet - Domain Regression and Predictive Inference in Psychiatric Neuroimaging
نویسندگان
چکیده
where sxβ is the sample variance of x T 1 β, . . . ,x T nβ, representing variance explained by the model, and R2 is the specified value (0.1 or 0.5). The left side of (A2) is similar to what Tibshirani and Knight (1999) called the “theoretical R2,” and has the interpretation that for responses generated according to (A1), (A2), the coefficient of determination for the true model is approximately equal to the specified value R2. An “R2 analogue” for logistic regression (Menard, 2000) is given by
منابع مشابه
Wavelet-domain Regression and Predictive Inference in Psychiatric Neuroimaging.
An increasingly important goal of psychiatry is the use of brain imaging data to develop predictive models. Here we present two contributions to statistical methodology for this purpose. First, we propose and compare a set of wavelet-domain procedures for fitting generalized linear models with scalar responses and image predictors: sparse variants of principal component regression and of partia...
متن کاملADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AND STEPWISE REGRESSION FOR COMPRESSIVE STRENGTH ASSESSMENT OF CONCRETE CONTAINING METAKAOLIN
In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training an...
متن کاملOn Prior Distributions and Approximate Inference for Structured Variables
We present a general framework for constructing prior distributions with structured variables. The prior is defined as the information projection of a base distribution onto distributions supported on the constraint set of interest. In cases where this projection is intractable, we propose a family of parameterized approximations indexed by subsets of the domain. We further analyze the special ...
متن کاملThe use of wavelet - artificial neural network and adaptive neuro fuzzy inference system models to predict monthly precipitation
Precipitation forecasting due to its random nature in space and time always faced with many problems and this uncertainty reduces the validity of the forecasting model. Nowadays nonlinear networks as intelligent systems to predict such complex phenomena are widely used. One of the methods that have been considered in recent years in the fields of hydrology is use of wavelet transform as a moder...
متن کاملSupplement to Asymptotic Inference about Predictive Accuracy using High Frequency Data ∗
This supplement contains three appendices. Appendix A contains proofs of results in the main text. Appendix B provides details for the stepwise procedures discussed in Section 5 of the main text. Appendix C contains some additional simulation results. ∗Contact address: Department of Economics, Duke University, 213 Social Sciences Building, Box 90097, Durham NC 27708-0097, USA. Email: jl410@duke...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015